JanusGraph Integrations

Elastic is a search company. Elasticsearch, Kibana Beats, Logstash, and Elasticsearch are the founders of the ElasticStack. These SaaS offerings allow data to be used in real-time and at scale for analytics, security, search, logging, security, and search. Elastic has over 100,000 members in 45 countries. Elastic's products have been downloaded more than 400 million times since their initial release. Today, thousands of organizations including Cisco, eBay and Dell, Goldman Sachs and Groupon, HP and Microsoft, as well as Netflix, Uber, Verizon and Yelp use Elastic Stack and Elastic Cloud to power mission critical systems that generate new revenue opportunities and huge cost savings. Elastic is headquartered in Amsterdam, The Netherlands and Mountain View, California. It has more than 1,000 employees in over 35 countries.

The Apache Cassandra database provides high availability and scalability without compromising performance. It is the ideal platform for mission-critical data because it offers linear scalability and demonstrated fault-tolerance with commodity hardware and cloud infrastructure. Cassandra's ability to replicate across multiple datacenters is first-in-class. This provides lower latency for your users, and the peace-of-mind that you can withstand regional outages.

Solr is highly reliable, scalable, and fault-tolerant. It provides distributed indexing, replication, load-balanced querying and automated failover and recovery. Solr powers many of the largest internet sites around the world's search and navigation functions. Solr allows powerful matching capabilities, including phrases, wildcards and joins, grouping, and much more across any type of data. Solr has been proven on large scales all over the globe. Solr uses the same tools that you use to make application development easy. Solr ships with an intuitive, responsive administrative interface that makes it easy to manage your Solr instances. Want to know more about your instances? Solr publishes loads metric data via JMX. Solr is built on Apache Zookeeper, which has been proven to scale well. Solr is a complete solution for replication, distribution, rebalancing, and fault tolerance.

G.V() is an all in one Gremlin IDE that allows you to write, debug and test your Gremlin graph database. It has a rich UI with graph visualization, editing, and connection management. G.V() automatically detects the connection requirements based upon the hostname you provide. It prompts you to enter the next required information so that you can have an easy onboarding experience regardless of which Gremlin database it is. To build, test, visualize, and query your data quickly, load, visualize, and draw your graph in true "What you see is what you get" fashion. Learn Gremlin using the embedded documentation and G.V()’s in-memory diagram. You can view your Gremlin query results quickly in different formats. Compatible with all major Apache TinkerPop enabled Graph Data Database Providers: Amazon Neptune; Azure Cosmos DB’s Gremlin API; DataStax Enterprise Graph; JanusGraph, ArcadeDB; Aliyun TairForGraph; Gremlin Server.

Graphlytic is a web-based BI platform that allows knowledge graph visualization and analysis. Interactively explore the graph and look for patterns using the Cypher query language or query templates for non-technical users. Users can also use filters to find answers to any graph question. The graph visualization provides deep insights into industries such as scientific research and anti-fraud investigation. Even users with little knowledge of graph theory can quickly explore the data. Cytoscape.js allows graph rendering. It can render tens to thousands of nodes and hundreds upon thousands of relationships. The application is available in three formats: Desktop, Cloud, or Server. Graphlytic Desktop is a Neo4j Desktop app that can be installed in just a few mouse clicks. Cloud instances are great for small teams who don't want or need to worry about installing and need to be up and running quickly.

Hackolade is the pioneer for data modeling of NoSQL and multi-model databases, providing a comprehensive suite of data modeling tools for various NoSQL databases and APIs. Hackolade is the only data modeling tool for MongoDB, Neo4j, Cassandra, ArangoDB, BigQuery, Couchbase, Cosmos DB, Databricks, DocumentDB, DynamoDB, Elasticsearch, EventBridge Schema Registry, Glue Data Catalog, HBase, Hive, Firebase/Firestore, JanusGraph, MariaDB, MarkLogic, MySQL, Oracle, PostgreSQL, Redshift, ScyllaDB, Snowflake, SQL Server, Synapse, TinkerPop, YugabyteDB, etc. It also applies its visual design to Avro, JSON Schema, Parquet, Protobuf, Swagger and OpenAPI, and is rapidly adding new targets for its physical data modeling engine. The software is user-friendly and simple to use yet provides powerful visuals and graphic data modeling to smooth the onboarding of NoSQL technology. Its software tools help functional analysts, designers, architects, and DBAs involved with NoSQL technology achieve greater transparency and control, resulting in reduced development time, increased application quality, and lower execution risks across the enterprise.

KgBase (or Knowledge Graph Base) is a robust, collaborative database that allows for versioning, analytics, visualizations, and visualizations. KgBase allows anyone to create knowledge graphs and gain insights about their data. You can import your CSVs or spreadsheets or use our API to collaborate on data. KgBase allows you to create no-code knowledge graphs. Our easy-to-use UI lets users navigate the graph and display the results in tables and charts. You can play with your graph data. You can build your query and watch the results change in real-time. It's similar to writing query code in Cypher and Gremlin, but much easier. It's also fast. You can view your graph as a table. This allows you to view all results, regardless of their size. KgBase is great for large graphs (millions) as well as simple projects. You can either use the cloud or self-hosted and have extensive database support. You can introduce graphs to your organization by seeding graphs from a template. Any query results can be easily converted into a chart visualization.

Berkeley DB is a set of embedded key-value databases libraries that provide high-performance data management services for applications.

Google Cloud Bigtable provides a fully managed, scalable NoSQL data service that can handle large operational and analytical workloads. Cloud Bigtable is fast and performant. It's the storage engine that grows with your data, from your first gigabyte up to a petabyte-scale for low latency applications and high-throughput data analysis. Seamless scaling and replicating: You can start with one cluster node and scale up to hundreds of nodes to support peak demand. Replication adds high availability and workload isolation to live-serving apps. Integrated and simple: Fully managed service that easily integrates with big data tools such as Dataflow, Hadoop, and Dataproc. Development teams will find it easy to get started with the support for the open-source HBase API standard.

Create graph visualization products that transform connected data into insight. JavaScript's flexibility and power allows you to quickly and easily create graph visualization applications that can go anywhere. KeyLines allows you to create graph visualization applications in a flexible way. Create interactive graph visualization tools that reveal hidden insights and threats. KeyLines JavaScript graph visual toolkit allows you to create applications that are tailored for your users, your data and the questions you need. It works with any browser, device or server and includes clear tutorials, demos and API documentation. With our developer support, you will quickly discover network insight. KeyLines makes it easy for you to create high-performance JavaScript graph visualization tools which work anywhere. They use HTML5 and WebGL graphics rendering, and carefully crafted code to provide users with quick and insightful visualization.

React graph visualization products can transform connected data into insight. ReGraph's data-driven API makes it easy to add graph visualizations into your React applications. Your users can get high-performance graph visualizations that are custom made, no matter where they are. ReGraph is a simple and easy coding experience for React developers. It features familiar logic, simple state handling, and well-documented Props. You can control where your data is stored and how the component behaves. It can be used in any browser on any device and integrates easily with any server or database. It allows you to create a custom React graph visualization app. ReGraph makes it easy for you to create powerful React graph visualization apps. Everything has been optimized for performance, right from the layout algorithms to the supercharged graphics rendering engine.

Apache HBase™, is used when you need random, real-time read/write access for your Big Data. This project aims to host very large tables, billions of rows and X million columns, on top of clusters of commodity hardware.

Apache Spark™, a unified analytics engine that can handle large-scale data processing, is available. Apache Spark delivers high performance for streaming and batch data. It uses a state of the art DAG scheduler, query optimizer, as well as a physical execution engine. Spark has over 80 high-level operators, making it easy to create parallel apps. You can also use it interactively via the Scala, Python and R SQL shells. Spark powers a number of libraries, including SQL and DataFrames and MLlib for machine-learning, GraphX and Spark Streaming. These libraries can be combined seamlessly in one application. Spark can run on Hadoop, Apache Mesos and Kubernetes. It can also be used standalone or in the cloud. It can access a variety of data sources. Spark can be run in standalone cluster mode on EC2, Hadoop YARN and Mesos. Access data in HDFS and Alluxio.

Atlas is a flexible and extensible set core foundational governance services that enable enterprises to efficiently and effectively meet their compliance requirements within Hadoop. It also allows integration with the entire enterprise data ecosystem. Apache Atlas offers open metadata management and governance capabilities that allow organizations to create a catalog of their data assets, classify, govern and provide collaboration capabilities around these assets for data scientists, analysts, and the data governance group. Pre-defined types to manage various Hadoop and non Hadoop metadata. Ability to create new types to manage metadata. Types can inherit from other types, and can have simple attributes, complex attributes, and object references. Type instances, also known as entities, are able to capture metadata object details and their relationships. REST APIs allow for easier integration with types and instances.